This invention relates to a method of dynamic control for a process or series of processes, in an industrial environment, for example, in a petroleum refining or processing plant.
In industrial plants, it is important to minimize losses which are inherent in the processes being performed therein while at the same time maximizing profits. This loss minimization/profit maximization is achieved via the technique of linear programming optimization, commonly referred to as L-P optimization. With the advent of successful L-P optimization of processes in an on-line environment, it has become possible to optimize plant operations using small on-line computers. Optimization is normally repeated every 3 or 4 hours so that approximately six times per day, the profit derivable from the process can be increased by shifting the singular unit under control from one operating point to another. Generally, profit can be increased by pushing the operation as close as possible to system constraints, such as temperature, pressure or flow rate constraints. How close one can approach these constraints becomes a measure of the efficiency of the process control being utilized. Efficiency of the controller in moving from one operating point to another also becomes important. Assuming that L-P operating points lie close to, or actually on system constraints, the controller must be able to move from one point to the other without violating these constraints. As the controller's ability to adequately perform these tasks decreases, the operating points must retreat from the L-P dictated operating points thus causing profit loss. Good control allows the user to minimize this profit loss.
Feed forward control becomes important in the optimization of processes since the user may initiate controller action based upon a prediction of where the outputs, or controlled variables, are going. This is superior to waiting until the process disturbances have actually changed the controlled variables before controller action is initiated. Hence, an ideal controller should have significant feed forward as well as ample feedback action. In addition, the control method should be able to deal with constraints and constraint violations in a real time fashion. In general, the existing control systems are limited Proportional/Integral (P/I) controllers and ratio controllers. These may be found in both cascade and feed forward loops. A P/I controller may consist of a temperature controller cascaded to a flow controller such as for heat medium flow control to fractionation column reboilers. A typical example of the use of a ratio controller would be ratio controlling the reflux to a fractionation column based upon feed rate to the column.
Other than the initial tuning of these controllers, they are completely ignorant of their own limitations as well as the conditions existing elsewhere on the unit being controlled. Hence, a condition of column over-pressuring due to maintenance of tray temperature set point in the outer loop of a heat medium controller may result when a column upstream to the column under control passes excessive light material out its bottom, said bottom's flow being the feed to the column under control. In this case, suitable intervention of a human operator is needed to alleviate the problem. On more complicated operating units, the appropriate action to be taken by a human operator to alleviate a problem condition may not be so readily apparent.
Other problems with existing systems may occur due to the size of process disturbances. Although the local P/I controllers operate reasonably well in the absence of large scale disturbances, the situation changes when the unit is subjected to large disturbances such as bringing a cracking furnace down for de-coking in an olefin unit where 10 to 15% feed flow disturbances are considered usual. Oscillations of conventional controllers also give rise to problems. When the conventional optimization control procedure is interfaced with the unit, trouble may occur when the optimization control drives continuously against operating constraints and the P/I controller, with its inherent oscillatory character, forces the optimization control to retreat from the constraint, thus decreasing net derivable profit from the unit.